Whisper Small Dv - Raj Vardhan
This model is a fine-tuned version of openai/whisper-small on the Common Voice 13 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2938
- Wer Ortho: 57.8522
- Wer: 11.0391
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.0596 | 1.6287 | 500 | 0.1694 | 61.1045 | 11.9414 |
| 0.021 | 3.2573 | 1000 | 0.1984 | 57.7547 | 11.6598 |
| 0.0168 | 4.8860 | 1500 | 0.2246 | 58.1378 | 11.6546 |
| 0.0079 | 6.5147 | 2000 | 0.2520 | 57.3508 | 11.2216 |
| 0.0056 | 8.1433 | 2500 | 0.2669 | 57.9079 | 11.2042 |
| 0.0049 | 9.7720 | 3000 | 0.2751 | 57.1419 | 11.1573 |
| 0.0047 | 11.4007 | 3500 | 0.2803 | 56.9956 | 11.0269 |
| 0.0044 | 13.0293 | 4000 | 0.2938 | 57.8522 | 11.0391 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu118
- Datasets 3.1.0
- Tokenizers 0.20.1
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openai/whisper-small